This disclosure relates generally to presenting content to users of an online system, and more specifically to presenting content to a group of users of the online system subject to limitations on a number of times certain content is presented within a time interval.
Online systems, such as social networking systems, allow users to connect to and to communicate with other users of the online system. Users may create profiles on an online system that are tied to their identities and include information about the users, such as interests and demographic information. The users may be individuals or entities such as corporations or charities. Online systems allow users to easily communicate and to share content with other online system users by providing content to an online system for presentation to other users. Content provided to an online system by a user may be declarative information provided by a user, status updates, check-ins to locations, images, photographs, videos, text data, or any other information a user wishes to share with additional users of the online system. An online system may also generate content for presentation to a user, such as content describing actions taken by other users on the online system.
When selecting content items for presentation to users, many online systems account for ratings or quality scores of content items. Ratings for content items are received from users of the online system may describe a user approval or disapproval of the content included in content items, describe likelihood of users interacting with the content included in content items, describe user assessment of whether content of content items is appropriate or inappropriate, or describe any other user reaction to the content of the content items. Based on ratings received for various content items, an online system may generate or train a model that determines a quality score for content items based on characteristics of content items and ratings received from users for content items having various characteristics.
Many online systems receive ratings for presented content items from a specific group of users. However, different users of the group often have different biases that affect how different users rate content items. These user-specific ratings biases may cause significant variation in how different users of the group rate similar content items. Hence, divergent ratings of a content item from different users of the group may be influenced more by particular biases of the different users than by characteristics of the content item itself. Accordingly, such user-specific biases in rating content items may impair training of a model for subsequent selection of content items by an online system that limits user interaction with the subsequently selected content items.